# Workers Profiling

Profile or debug CPU usage and memory allocation in deployed Cloudflare Workers and...

- Repository: https://github.com/cloudflare/skills (3246 stars)
- Category: Testing
- License: Apache-2.0
- Last updated: 2026-10-31
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add cloudflare/skills --skill workers-profiling -g -a claude-code -y`
Codex: `npx skills add cloudflare/skills --skill workers-profiling -g -a codex -y`
Cursor: `npx skills add cloudflare/skills --skill workers-profiling -g -a cursor -y`
Gemini CLI: `npx skills add cloudflare/skills --skill workers-profiling -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add cloudflare/skills`

## Description

Profile or debug CPU usage and memory allocation in deployed Cloudflare Workers and Durable Objects. Then use this information to optimize your code.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Workers profiling

Find expensive functions or memory allocations in deployed code and come up with ways to fix them.

## Retrieve the docs

Start with the [production profiling guide](https://developers.cloudflare.com/workers/observability/profiling-in-production/index.md) to understand how
Workers and Durable Objects profiling works.

## Profiling steps

1. Identify the symptom and affected workload: CPU usage, latency, allocation pressure, or memory growth.
2. Confirm the account, Worker, environment, and deployed version with the user.
3. For a Durable Object, also confirm its owning Worker, namespace, and instance.
4. Choose CPU or heap profiling from the current guide's supported types and meanings.

Where possible, use the [`cf` CLI](https://developers.cloudflare.com/cf/index.md) to capture profiles. If the user requests `cf`, inspect the installed version's command help and schema where available.

If `cf` isn't available, consider prompting the user whether they would like to install it.


The profiling API will return a pprof file which you can analyze directly, or using appropriate tools like Go's `pprof` utility.

## Inspect the evidence

- Read the pprof file and analyse it for hotspots
- Map hotspots to functions and source locations when evidence supports it; report missing symbols or source mappings.
- If filenames and function names are pointing at the generated JavaScript, consider suggesting to the user to enable source maps and re-do the profiling.

## Optimise

Propose the smallest code change supported by the capture which resolves the issues identified.

## Report findings

Return a concise report with:

- Evidence for each finding: file, function, source location, and metric with units, where available.
- The smallest actionable change and how to check its effect.

## Skill feedback

The rest: https://github.com/cloudflare/skills/blob/HEAD/skills/workers-profiling/SKILL.md